Professor Moore gave a carefully detailed argument about why educational institutions (particularly higher ed) had to change, given the changes in society. He then argued some of the changes needed, and suggested some new institutional structure models that might provide guidance.
The legendary Steve “The Woz” Wozniak was the opening keynote at the 3rd International Conference of e-Learning and Distance Learning. In a wide-ranging, engaging, and personal speech, Steve made a powerful plea for the value of the thoughtful learner and intrinsic motivation, project-based learning, social, and self-paced learning.
Recently, there’s been a lot of talk and excitement about unlearning, and it’s always rubbed me the wrong way. Because, frankly, unlearning physiologically isn’t really an option. So I thought I’d talk about the cognitive processes, and then look at what folks are talking about.
Learning has been cutely characterized as “neurons that fire together, wire together”. And that’s really it: learning is about strengthening associations between patterns (which is why you can only learn so much at one time and then need to sleep, that strengthening effect only takes so much at one shot). We start with conscious effort and compile it down below conscious level.
However, you can’t really weaken those associations! So, you simply can’t unlearn. What really happens, as Dr. Jane Bozarth suggests, is: “overwriting existing knowledge or skill, or just pushing it to the background to accommodate something new, or rewiring pathways”. And points out that it’s hard work.
In short, unlearning is really relearning. And it’s harder because you need to overcome prior experience, strengthen the associations of the new beyond the existing strength of the old. And it’s important that, if things have changed, or previous experience or instinct will lead you elsewhere, you need to make sure that you’ve now got learners making the decisions in the effective ways. Which may mean modifying, not necessarily just replacing, but it does take conscious effort in analysis and design, diagnosing misconceptions, figuring appropriate levels of practice, etc.
So why this excitement about unlearning? It appears people are having fun with words. They’re using the phrase to mean something else. Take, for instance, this definition:
“Unlearning is not exactly letting go of our knowledge or perceptions, but rather stepping outside our perceptions to stand apart from our world views and open up new lenses to interpret and learn about the world.” – Erica Dhawan
Um, okay. The same article quotes Prasad Kaipa as saying “we generate anew rather than reformulate the same old stuff”. So, it’s about a different perspective. That’s valuable. Why call it unlearning then? It could be a step to unlearning, looking afresh and seeing new opportunities for different ways of doing things, but it’s not really unlearning.
So I see no reason to mislead people. Learning is rewarding, and touting things as unlearning make it seem as straightforward as learning, but relearning a new way is harder. The use of the term seems to minimize the effort required. And using the term to mean something else seems misleading. If you want to talk about shifting perspectives, do so!
What am I missing? Until I find a better explanation than what I’ve found, I’m calling out the term. Genially, of course.
It is increasingly evident that as we unpack how we get the best results from thinking, we don’t do it alone. Moreover, the elements that contribute emphasize diversity. Two synergistic events highlight this.
First, my colleague Harold Jarche has an interesting post riffing off of Stephen Johnson’s new book, Future Perfect. In looking at patterns that promote more effective decision making, an experiment is cited. In that study, a diverse group of lower intelligence produces better outputs than a group of relatively homogenous smart folks. They quote Scott Page, saying “Diversity trumps ability”. Hear hear.
This resonated particularly in light of an article I discovered last week that talked about Tom Malone’s work on looking at what he calls “collective intelligence“. In it, Tom says “Our future as a species may depend on our ability to use our global collective intelligence to make choices that are not just smart, but also wise.” I couldn’t agree more, and am very interested in the wisdom part. Of interest in the article is a series of studies he did looking at what led to better outputs from groups, and they debunked a number of obvious factors including the above issue of intelligence. Two compelling features were the social perceptiveness of the group, e.g. how well they tuned in to what other members of the group thought, and how even the turn-taking was. The more everyone had an equal chance to talk (instead of a one-sided conversation), and the more socially aware the group, the better the output. Interestingly, which he correlated to the socially aware, was that the more women the better!
The point being that learning social skills, using good meeting processes, and emphasizing diversity, all actions similar to those needed for effective learning organizations, lead to better decision making. If you want good decisions, you need to break down hierarchies, open up the conversation channels, and listen. We have good science about practices that lead to effective outcomes for organizations. Are you practicing them?
David Jonassen passed away on Sunday. He had not only a big impact on the field of computers for learning, but also on learning itself. And he was a truly nice person.
I had early on been a fan of his work, his writing on computers as cognitive tools was insightful. He resisted the notion of teaching computing, and instead saw computers as mind tools, enablers of thinking. He was widely and rightly regarded as an influential innovator for this work.
I also regularly lauded his work on problem-solving. The one notion that really resonated was that the problems we give to kids in schools (and too often to adults in training) bear little resemblance to the problems they’ll face outside. He did deep work on problem-solving that more should pay attention to. He demonstrated that you could get almost as good a performance on standard tests using meaningful problems, and you got much better results on problem-solving skills (21st century skills) as well. I continue to apply his principles in my learning design strategies.
I had the opportunity to meet him face to face at a conference on learning in organizations. While I was rapt in his presentation, somehow it didn’t work for the audience as a whole, a shame. Still, I had the opportunity to finally talk to him, and it was a real pleasure. He was humble, thoughtful, and really willing to engage. I subsequently shared a stage with him when he presented virtually to a conference I was at live, and was thrilled to have him mention he was using my game design book in one of his classes.
He contributed greatly to my understanding, and to the field as a whole. He will be missed.
At the recent DevLearn, several of us gathered together in a Junto to talk about issues we felt were becoming important for our field. After a mobile learning panel I realized that, just as mlearning makes it too easy to think about ‘courses on a phone’, I worry that ‘learning experience design’ (a term I’ve championed) may keep us focused on courses rather than exploring the full range of options including performance support and eCommunity.
So I began thinking about performance experience design as a way to keep us focused on designing solutions to performance needs in the organization. It’s not just about what’s in our heads, but as we realize that our brains are good at certain things and not others, we need to think about a distributed cognition solution, looking at how resources can be ‘in the world’ as well as in others’ heads.
The next morning in the shower (a great place for thinking :), it occurred to me that what is needed is a design process before we start designing the solution. To complement Kahnemann’s Thinking Fast and Slow (an inspiration for my thoughts on designing for how we really think and learn), I thought of designing backward and forward. Let me try to make that concrete.
What I’m talking about is starting with a vision of what performance would look like in an ideal world, working backward to what can be in the world, and what needs to be in the head. We want to minimize the latter. I want to respect our humanity in a way, allowing us to (choose to) do the things we do well, and letting technology take on the things we don’t want to do.
In my mind, the focus should be on what decisions learners should be making at this point, not what rote things we’re expecting them to do. If it’s rote, we’re liable to be bad at it. Give us checklists, or automate it!
From there, we can design forward to create those resources, or make them accessible (e.g. if they’re people). And we can design the ‘in the head’ experience as well, and now’s the time for learning experience design, with a focus on developing our ability to make those decisions, and where to find the resources when we need them. The goal is to end up designing a full performance solution where we think about the humans in context, not as merely a thinking box.
It naturally includes design that still reflects my view about activity-centered learning (which I’m increasingly convinced is grounded in cognitive research). Engaging emotion, distributed across platforms and time, using a richer suite of tools than just content delivery and tests. And it will require using something like Michael Allen’s Successive Approximation Model perhaps, recognizing the need to iterate.
I wanted to term this performance experience design, and then as several members workshopped this with me, I thought we should just call it performance design (at least externally, to stakeholders not in our field, we can call it performance experience design for ourselves). And we can talk about learning experience design within this, as well as information design, and social networks, and…
It’s really not much more than what HPT would involve, e.g. the prior consideration of what the problem is, but it’s very focused on reducing what’s in the head, including emotion in the learning when it’s developed, using social resources as well as performance support, etc. I think this has the opportunity to help us focus more broadly in our solution space, make us more relevant to the organization, and scaffold us past many of our typical limitations in approach. What do you think?
Last week I was on a panel about the API previously known as Tin Can at #DevLearn, and some thoughts crystallized. Touted as the successor to SCORM, it’s ridiculously simple: Subject Verb Object: e.g. “I did this”, such as ‘John Doe read Engaging Learning’ but also ‘Jane Doe took this picture’. And this has interesting implications.
First, the API itself is very simple, and while it can be useful on it’s own, it’ll be really useful when there’re tools around it. It’s just a foundation upon which things can be done. There’ll need to be places to record these actions, and ones to pull together sequences of recommendations for learning paths, and more. You’ll want to build portfolios of what you’ve done (not just what content you’ve touched).
But it’s about more than learning. These can cross accessing performance support resources, actions in social media systems, and more. This person touched that resource. That person edited this file. This other person commented.
One big interesting opportunity is to be able to start mining these. We can start looking at evidence of what folks did and finding good and bad outcomes. It’s a consistent basis for big data and analytics. It’s also a basis to start customizing: if the people who touched this resource were better able to solve problem X, other people with that problem maybe should also touch it. If they’ve already tried X and Y, we can next recommend Z. Personalization/customization.
An audience member asked what they should take back to their org, and who needed to know what. My short recommendations:
Developers need to start thinking about instrumenting everything. Everything people touch should report out on their activity. And then start aggregating this data. Mobile, systems, any technology touch. People can self report, but it’s better to the extent that it’s automated.
Managers need to recognize that they’re going to have very interesting opportunities to start tracking and mining information as a basis to start understanding what’s happening. Coupled with rich other models, like of content (hence the need for a content strategy), tasks, learners, we can start doing more things by rules.
And designers need to realize, and then take advantage of, a richer suite of options for learning experiences. Have folks take a photo of an example of X. You can ask them to discuss Y. Have them collaborate to develop a Z. You could even send your learners out to do a flash mob ;).
Learning is not about content, it’s about experience, and now we have ways to talk about it and track it. It’s just a foundation, just a standard, just plumbing, just a start, but valuable as all that.
Dayna used stories from her experience as a radio host to illuminate her points about how to be a rock star in life.
Jeffrey Ma gave a interesting talk on lessons from succeeding at blackjack that included both life lessons as well as lessons on data driven decision making.
It’s hard to capture the stories, humor, and riveting images of Alison’s inspiring talk, so I’ve only been able to record the lessons she passed on, but great stuff!
